Review credibility as a safeguard against fakery: the case of Amazon
研究基于亚马逊等平台数据，提出并验证了一种利用现有保障措施量化评论可信度的方法，能有效降低产品不确定性，并发现高可信度评论对产品销售有显著影响，尤其对利基和新产品更有效。
Online reviews remain a reliable source for customers when making purchase decisions. Yet, the pervasiveness of fake reviews jeopardises this reliability and questions the quality of this content. In this paper, we provide empirical evidence from a major online retailer that mitigation against fakery can be successful. To that end, we proposed, tested, and validated an approach, based on existing safeguards, to quantify the credibility of reviews and thus reliably reduce product uncertainty. We also showed that reviews with sufficient credibility signals were effective at influencing product sales, and this influence was prevalent for both niche and new products on the market. As such, this study offers a novel approach to mitigate the impact of fakery in reviews posted to online infomediaries. Our work focuses primarily on Amazon as a major retailer but also provides further support by drawing on Yelp, another major review platform.